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- Opinion Mining and Sentiment Analysis (6)
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- Expert Systems (4)
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Articles 1 - 11 of 11
Full-Text Articles in Physical Sciences and Mathematics
Semtiment Analysis On Youtube: A Brief Survey, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi, Afsana Khan
Semtiment Analysis On Youtube: A Brief Survey, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi, Afsana Khan
Dr. Muhammad Zubair Asghar
Sentiment analysis or opinion mining is the field of study related to analyze opinions, sentiments, evaluations, attitudes, and emotions of users which they express on social media and other online resources. The revolution of social media sites has also attracted the users towards video sharing sites, such as YouTube. The online users express their opinions or sentiments on the videos that they watch on such sites. This paper presents a brief survey of techniques to analyze opinions posted by users about a particular video.
Context-Aware Spelling Corrector For Sentiment Analysis, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi
Context-Aware Spelling Corrector For Sentiment Analysis, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi
Dr. Muhammad Zubair Asghar
One of the most thrived features of the Web 2.0 era is the fastest growing of user-generated content in the shape of blogs and reviews, with unmatched speed and size. These reviews contain poor, text quality and structure which results spelling mistakes as well as out-of-vocabulary words. This paper presents a Context-Aware Spelling Corrector for Sentiment Analysis based on similarity measures and statistical language model. The paper also presents some compelling statistics about spelling errors. The comparative results show that the proposed framework outperforms the related systems, features wise and in accuracy.
Lexicon-Based Sentiment Analysis In The Social Web, Fazal Masud Kundi, Dr. Muhammad Zubair Asghar
Lexicon-Based Sentiment Analysis In The Social Web, Fazal Masud Kundi, Dr. Muhammad Zubair Asghar
Dr. Muhammad Zubair Asghar
Sentiment analysis is a compelling issue for both information producers and consumers. We are living in the “age of customer”, where customer knowledge and perception is a key for running successful business. The goal of sentiment analysis is to recognize and express emotions digitally. This paper presents the lexicon-based framework for sentiment classification, which classifies tweets as a positive, negative, or neutral. The proposed framework also detects and scores the slangs used in the tweets. The comparative results show that the proposed system outperforms the existing systems. It achieves 92% accuracy in binary classification and 87% in multi-class classification.
Lexicon Based Approach For Sentiment Classification Of User Reviews, Dr. Muhammad Zubair Asghar
Lexicon Based Approach For Sentiment Classification Of User Reviews, Dr. Muhammad Zubair Asghar
Dr. Muhammad Zubair Asghar
With the advent of web, online user reviews are getting more and more attention of the researchers because valuable information about products and services are available on social media like twitter1. These reviews are very helpful for organizations as well as for new customers showing interest in these products or services. But this data is generated in tremendous amount which is out of control of manual mining methods. These reviews need a model that has the ability to gauge these shared reviews according to predefined categories. This work introduces a rule based approach to find the opinion classification of reviews. …
Detection And Scoring Of Internet Slangs For Sentiment Analysis Using Sentiwordnet, Dr. Muhammad Zubair Asghar
Detection And Scoring Of Internet Slangs For Sentiment Analysis Using Sentiwordnet, Dr. Muhammad Zubair Asghar
Dr. Muhammad Zubair Asghar
The online information explosion has created great challenges and opportunities for both information producers and consumers. Understanding customer’s feelings, perceptions and satisfaction is a key performance indicator for running successful business. Sentiment analysis is the digital recognition of public opinions, feelings, emotions and attitudes. People express their views about products, events or services using social networking services. These reviewers excessively use Slangs and acronyms to express their views. Therefore, Slang's analysis is essential for sentiment recognition. This paper presents a framework for detection and scoring of Internet Slangs (DSIS) using SentiWordNet in conjunction with other lexical resources. The comparative results …
Sentiment Classification Through Semantic Orientation Using Sentiwordnet, Dr. Muhammad Zubair Asghar, Dr, Auranzeb Khan
Sentiment Classification Through Semantic Orientation Using Sentiwordnet, Dr. Muhammad Zubair Asghar, Dr, Auranzeb Khan
Dr. Muhammad Zubair Asghar
Sentiment analysis is the procedure by which information is extracted from the opinions, appraisals and emotions of people in regards to entities, events and their attributes. In decision making, the opinions of others have a significant effect on customers ease in making choices regards to online shopping, choosing events, products, entities. In this paper, a rule based domain independent sentiment analysis method is proposed. The proposed method classifies subjective and objective sentences from reviews and blog comments. The semantic score of subjective sentences is extracted from SentiWordNet to calculate their polarity as positive, negative or neutral based on the contextual …
Diagnosis Of Skin Diseases Using Online Expert System, Dr. Muhammad Zubair Asghar, Muhammad Junaid Asghar
Diagnosis Of Skin Diseases Using Online Expert System, Dr. Muhammad Zubair Asghar, Muhammad Junaid Asghar
Dr. Muhammad Zubair Asghar
This paper describes Expert System (ES) for diagnosis and management of skin diseases. More than 13 types of skin diseases can be diagnosed and treated by our system. It is rule based web-supported expert system, assisting skin specialists, medical students doing specialization in dermatology, researchers as well as skin patients having computer know-how. System was developed with Java Technology. The expert rules were developed on the symptoms of each type of skin disease, and they were presented using tree-graph and inferred using forward-chaining with depth-first search method. User interaction with system is enhanced with efficient user interfaces. The web based …
Expert System For Online Diagnosis Of Red-Eye Diseases, Dr. Muhammad Zubair Asghar, Muhammad Junaid Asghar
Expert System For Online Diagnosis Of Red-Eye Diseases, Dr. Muhammad Zubair Asghar, Muhammad Junaid Asghar
Dr. Muhammad Zubair Asghar
This paper describes Expert System (ES) for online diagnosis and prescription of red-eye diseases. The types of eye diseases that can be diagnosed with this system are called Red-eye diseases i.e. disease in which red-eye is the common symptom. It is rule based web-supported expert system, assisting ophthalmologists, medical students doing specialization in ophthalmology, researchers as well as eye patients having computer know-how. System was designed and programmed with Java Technology. The expert rules were developed on the symptoms of each type of Red-eye disease, and they were presented using tree-graph and inferred using forward-chaining with depth-first search method. User …
Computer Assisted Diagnoses For Red Eye (Cadre), Dr. Muhammad Zubair Asghar
Computer Assisted Diagnoses For Red Eye (Cadre), Dr. Muhammad Zubair Asghar
Dr. Muhammad Zubair Asghar
This paper introduces an expert System (ES) named as “CADRE-Computer Assisted Diagnoses for Red Eye. Mostly the remote areas of the population are deprived of the facilities of having experts in eye disease. So it is the need of the day to store the expertise of Eye specialists in computers through using ES technology. This ES is a rule-based Expert System that assists in red-eye diagnosis and treatment. The knowledge acquired from literature review and human experts of the specific domain was used as a base for analysis, diagnosis and recommendations. CADRE evaluates the risk factors of 20 eye diseases …
Clustering-Based High Trend Identification In Dataset, Dr. Muhammad Zubair Asghar, Dr. Auranzeb Khan, Fazal Masud Kundi, Nafees Ur Rehman
Clustering-Based High Trend Identification In Dataset, Dr. Muhammad Zubair Asghar, Dr. Auranzeb Khan, Fazal Masud Kundi, Nafees Ur Rehman
Dr. Muhammad Zubair Asghar
Clustering data into meaningful groups has a vast scope of research in several fields, like: statistics, information theory, machine learning, databases, and bioinformatics. This paper presents the modified form of K-means clustering algorithm called T-means. This algorithm creates, sorted clusters and labels as "high trend" and "low trend". Then M cases are selected from the high trend cluster (HTC) to construct the final HTC. The algorithm was tested on real univariate data of student's marks. Experimental results show that T-means can be efficiently used to construct the sorted cluster of significant cases in data set. T-means will help to identify …
Inheritance Evaluation System Using Islamic Law, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi, Abdur Rashid Khan
Inheritance Evaluation System Using Islamic Law, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi, Abdur Rashid Khan
Dr. Muhammad Zubair Asghar
The research work about the Inheritance Evaluation System using Islamic law is valuable for automatic calculation of share out of total inheritance of a deceased to his/her legal heir(s). First version of the software named as Islamic Inheritance Evaluation System (IIES) deals with Hanfi School of thought. IIES may solve the heritage problem of heirs in text as well as in graphical form at home without establishing a suit in any court. This also leads to further research of who is how much related to whom?